Multi-omic single-cell snapshots reveal multiple independent trajectories to drug tolerance in a melanoma cell line.
Cell Line, Tumor
Drug Tolerance
Genes, Reporter
Genomics
Green Fluorescent Proteins
/ metabolism
Humans
Melanoma
/ drug therapy
Metabolomics
Microphthalmia-Associated Transcription Factor
Models, Molecular
Proteomics
Proto-Oncogene Proteins B-raf
/ genetics
Reproducibility of Results
Single-Cell Analysis
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
11 05 2020
11 05 2020
Historique:
received:
03
04
2019
accepted:
02
04
2020
entrez:
13
5
2020
pubmed:
13
5
2020
medline:
6
8
2020
Statut:
epublish
Résumé
The determination of individual cell trajectories through a high-dimensional cell-state space is an outstanding challenge for understanding biological changes ranging from cellular differentiation to epigenetic responses of diseased cells upon drugging. We integrate experiments and theory to determine the trajectories that single BRAF
Identifiants
pubmed: 32393797
doi: 10.1038/s41467-020-15956-9
pii: 10.1038/s41467-020-15956-9
pmc: PMC7214418
doi:
Substances chimiques
Microphthalmia-Associated Transcription Factor
0
Green Fluorescent Proteins
147336-22-9
Proto-Oncogene Proteins B-raf
EC 2.7.11.1
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2345Subventions
Organisme : NCI NIH HHS
ID : U01 CA217655
Pays : United States
Organisme : NCI NIH HHS
ID : F99 CA212231
Pays : United States
Organisme : NCI NIH HHS
ID : U54 CA209971
Pays : United States
Organisme : NCI NIH HHS
ID : P01 CA244118
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM007266
Pays : United States
Organisme : NCI NIH HHS
ID : P01 CA168585
Pays : United States
Organisme : NCI NIH HHS
ID : R35 CA197633
Pays : United States
Organisme : NCI NIH HHS
ID : U54 CA199090
Pays : United States
Références
Chapman, P. B. et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N. Engl. J. Med. 364, 2507–2516 (2011).
pubmed: 21639808
pmcid: 21639808
doi: 10.1056/NEJMoa1103782
Ramirez, M. et al. Diverse drug-resistance mechanisms can emerge from drug-tolerant cancer persister cells. Nat. Commun. 7, 10690 (2016).
Pisco, A. O. et al. Non-Darwinian dynamics in therapy-induced cancer drug resistance. Nat. Commun. 4, 2467 (2013).
Salgia, R. & Kulkarni, P. The genetic/non-genetic duality of drug ‘resistance’ in cancer. Trends Cancer 4, 110–118 (2018).
pubmed: 29458961
pmcid: 5822736
doi: 10.1016/j.trecan.2018.01.001
Shaffer, S. M. et al. Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature 546, 431–435 (2017).
pubmed: 28607484
pmcid: 28607484
doi: 10.1038/nature22794
Liau, B. B. et al. Adaptive chromatin remodeling drives glioblastoma stem cell plasticity and drug tolerance. Cell Stem Cell 20, 233–246.e7 (2017).
pubmed: 27989769
doi: 10.1016/j.stem.2016.11.003
Hugo, W. et al. Non-genomic and immune evolution of melanoma acquiring MAPKi resistance. Cell 162, 1271–1285 (2015).
pubmed: 26359985
pmcid: 4821508
doi: 10.1016/j.cell.2015.07.061
Su, Y. et al. Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance. PLoS Comput. Biol. https://doi.org/10.1371/journal.pcbi.1007034 (2019).
doi: 10.1371/journal.pcbi.1007034
pubmed: 31483777
pmcid: 6752863
Fallahi-Sichani, M. et al. Systematic analysis of BRAFV600E melanomas reveals a role for JNK/c-Jun pathway in adaptive resistance to drug-induced apoptosis. Mol. Syst. Biol. 11, 797–797 (2015).
pubmed: 25814555
doi: 10.15252/msb.20145877
Su, Y. et al. Single-cell analysis resolves the cell state transition and signaling dynamics associated with melanoma drug-induced resistance. Proc. Natl Acad. Sci. USA 114, 13679–13684 (2017).
Tsoi, J. et al. Multi-stage differentiation defines melanoma subtypes with differential vulnerability to drug-induced iron-dependent oxidative stress. Cancer Cell 33, 890–904.e5 (2018).
pubmed: 29657129
pmcid: 5953834
doi: 10.1016/j.ccell.2018.03.017
Ramsdale, R. et al. The transcription cofactor c-JUN mediates phenotype switching and BRAF inhibitor resistance in melanoma. Sci. Signal. 8, ra82 (2015).
pubmed: 26286024
doi: 10.1126/scisignal.aab1111
Nazarian, R. et al. Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation. Nature 468, 973–977 (2010).
pubmed: 21107323
pmcid: 3143360
doi: 10.1038/nature09626
Walsh, A. M. et al. Sprouty2 drives drug resistance and proliferation in glioblastoma. Mol. Cancer Res. 13, 1227–1237 (2015).
pubmed: 25934697
pmcid: 4679183
doi: 10.1158/1541-7786.MCR-14-0183-T
Buonato, J. M. & Lazzara, M. J. ERK1/2 blockade prevents epithelial-mesenchymal transition in lung cancer cells and promotes their sensitivity to EGFR inhibition. Cancer Res. 74, 309–319 (2014).
pubmed: 24108744
doi: 10.1158/0008-5472.CAN-12-4721
Titz, B. et al. JUN dependency in distinct early and late BRAF inhibition adaptation states of melanoma. Cell Discov. 2, 16028 (2016).
Wei, W. et al. Single-cell phosphoproteomics resolves adaptive signaling dynamics and informs targeted combination therapy in glioblastoma. Cancer Cell 29, 563–573 (2016).
pubmed: 27070703
pmcid: 4831071
doi: 10.1016/j.ccell.2016.03.012
Meyer, A. S., Miller, M. A., Gertler, F. B. & Lauffenburger, D. A. The receptor AXL diversifies EGFR signaling and limits the response to EGFR-targeted inhibitors in triple-negative breast cancer cells. Sci. Signal. 6, ra66 (2013).
Lazzara, M. J. et al. Impaired SHP2-mediated extracellular signal-regulated kinase activation contributes to gefitinib sensitivity of lung cancer cells with epidermal growth factor receptor-activating mutations. Cancer Res. 70, 3843–3850 (2010).
pubmed: 20406974
pmcid: 2862125
doi: 10.1158/0008-5472.CAN-09-3421
Ratnikov, B. I., Scott, D. A., Osterman, A. L., Smith, J. W. & Ronai, Z. A. Metabolic rewiring in melanoma. Oncogene 36, 147–157 (2017).
pubmed: 27270434
doi: 10.1038/onc.2016.198
Parmenter, T. J. et al. Response of BRAF-mutant melanoma to BRAF inhibition is mediated by a network of transcriptional regulators of glycolysis. Cancer Discov. 4, 423–433 (2014).
pubmed: 24469106
pmcid: 4110245
doi: 10.1158/2159-8290.CD-13-0440
Luo, C. et al. A PGC1α-mediated transcriptional axis suppresses melanoma metastasis. Nature 537, 422–426 (2016).
pubmed: 27580028
pmcid: 5161587
doi: 10.1038/nature19347
Pan, M. et al. Regional glutamine deficiency in tumours promotes dedifferentiation through inhibition of histone demethylation. Nat. Cell Biol. 18, 1090–1101 (2016).
pubmed: 27617932
pmcid: 5536113
doi: 10.1038/ncb3410
Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
pubmed: 26000488
pmcid: 26000488
doi: 10.1016/j.cell.2015.05.002
Bendall, S. C. et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332, 687–696 (2011).
pubmed: 21551058
pmcid: 3273988
doi: 10.1126/science.1198704
Ma, C. et al. A clinical microchip for evaluation of single immune cells reveals high functional heterogeneity in phenotypically similar T cells. Nat. Med. 17, 738–743 (2011).
pubmed: 21602800
pmcid: 3681612
doi: 10.1038/nm.2375
Heath, J. R., Ribas, A. & Mischel, P. S. Single-cell analysis tools for drug discovery and development. Nat. Rev. Drug Discov. 15, 204–216 (2016).
pubmed: 26669673
doi: 10.1038/nrd.2015.16
Su, Y., Shi, Q. & Wei, W. Single cell proteomics in biomedicine: high-dimensional data acquisition, visualization, and analysis. Proteomics 17 (2017).
Levine, J. H. et al. Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis. Cell 162, 184–197 (2015).
pubmed: 26095251
pmcid: 4508757
doi: 10.1016/j.cell.2015.05.047
Azizi, E. et al. Single-cell map of diverse immune phenotypes in the breast tumor microenvironment. Cell 174, 1293–1308.e36 (2018).
pubmed: 29961579
pmcid: 6348010
doi: 10.1016/j.cell.2018.05.060
Rambow, F. et al. Toward minimal residual disease-directed therapy in melanoma. Cell 174, 843–855.e19 (2018).
pubmed: 30017245
doi: 10.1016/j.cell.2018.06.025
pmcid: 30017245
Bendall, S. C. et al. Single-cell trajectory detection uncovers progression and regulatory coordination in human b cell development. Cell 157, 714–725 (2014).
pubmed: 24766814
pmcid: 4045247
doi: 10.1016/j.cell.2014.04.005
Setty, M. et al. Wishbone identifies bifurcating developmental trajectories from single-cell data. Nat. Biotechnol. 34, 637–645 (2016).
pubmed: 27136076
pmcid: 4900897
doi: 10.1038/nbt.3569
Haghverdi, L., Büttner, M., Wolf, F. A., Buettner, F. & Theis, F. J. Diffusion pseudotime robustly reconstructs lineage branching. Nat. Methods 13, 845–848 (2016).
pubmed: 27571553
doi: 10.1038/nmeth.3971
pmcid: 27571553
Schiebinger, G. et al. Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming. Cell https://doi.org/10.1016/j.cell.2019.01.006 (2019).
Lin, Y., Sohn, C. H., Dalal, C. K., Cai, L. & Elowitz, M. B. Combinatorial gene regulation by modulation of relative pulse timing. Nature 527, 54–58 (2015).
pubmed: 26466562
pmcid: 4870307
doi: 10.1038/nature15710
Young, J. W. et al. Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy. Nat. Protoc. 7, 80–88 (2012).
doi: 10.1038/nprot.2011.432
Comandante-Lou, N., Khaliq, M., Venkat, D., Manikkam, M. & Fallahi-Sichani, M. Phenotype-based probabilistic analysis of heterogeneous responses to cancer drugs and their combination efficacy. PLoS Comput. Biol. 16, e1007688 (2020).
pubmed: 32084135
pmcid: 7055924
doi: 10.1371/journal.pcbi.1007688
Lassen, A. et al. Effects of AKT inhibitor therapy in response and resistance to BRAF inhibition in melanoma. Mol. Cancer https://doi.org/10.1186/1476-4598-13-83 (2014).
Shi, Q. et al. Single-cell proteomic chip for profiling intracellular signaling pathways in single tumor cells. Proc. Natl Acad. Sci. USA 109, 419–424 (2012).
pubmed: 22203961
doi: 10.1073/pnas.1110865109
Wei, W. et al. Hypoxia induces a phase transition within a kinase signaling network in cancer cells. Proc. Natl Acad. Sci. USA 110, E1352–E1360 (2013).
pubmed: 23530221
doi: 10.1073/pnas.1303060110
Xue, M. et al. Chemical methods for the simultaneous quantitation of metabolites and proteins from single cells. J. Am. Chem. Soc. 137, 4066–4069 (2015).
Xue, M., Wei, W., Su, Y., Johnson, D. & Heath, J. R. Supramolecular probes for assessing glutamine uptake enable semi-quantitative metabolic models in single cells. J. Am. Chem. Soc. 138 (2016).
Bailey, R. C., Kwong, G. A., Radu, C. G., Witte, O. N. & Heath, J. R. DNA-encoded antibody libraries: a unified platform for multiplexed cell sorting and detection of genes and proteins. J. Am. Chem. Soc. 129, 1959–1967 (2007).
pubmed: 17260987
pmcid: 3677962
doi: 10.1021/ja065930i
Fallahi‐Sichani, M. et al. Adaptive resistance of melanoma cells to RAF inhibition via reversible induction of a slowly dividing de‐differentiated state. Mol. Syst. Biol. 13, 905 (2017).
pubmed: 28069687
pmcid: 5248573
doi: 10.15252/msb.20166796
Poovathingal, S. K., Kravchenko-Balasha, N., Shin, Y. S., Levine, R. D. & Heath, J. R. Critical points in tumorigenesis: a carcinogen-initiated phase transition analyzed via single-cell proteomics. Small 12, 1425–1431 (2016).
pubmed: 26780498
pmcid: 4886749
doi: 10.1002/smll.201501178
Zunder, E. R., Lujan, E., Goltsev, Y., Wernig, M. & Nolan, G. P. A continuous molecular roadmap to iPSC reprogramming through progression analysis of single-cell mass cytometry. Cell Stem Cell 16, 323–337 (2015).
pubmed: 25748935
pmcid: 4401090
doi: 10.1016/j.stem.2015.01.015
Amir, E. A. D. et al. ViSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat. Biotechnol. 31, 545–552 (2013).
pmcid: 4076922
doi: 10.1038/nbt.2594
pubmed: 4076922
Moon, K. R. et al. Visualizing structure and transitions in high-dimensional biological data. Nat. Biotechnol. https://doi.org/10.1038/s41587-019-0336-3 (2019).
Zadran, S., Arumugam, R., Herschman, H., Phelps, M. E. & Levine, R. D. Surprisal analysis characterizes the free energy time course of cancer cells undergoing epithelial-to-mesenchymal transition. Proc. Natl Acad. Sci. USA 111, 13235–13240 (2014).
pubmed: 25157127
doi: 10.1073/pnas.1414714111
Levine, R. D. Molecular Reaction Dynamics 9780521842 (Cambridge Univ. Press, 2005).
Remacle, F., Kravchenko-Balasha, N., Levitzki, A. & Levine, R. D. Information-theoretic analysis of phenotype changes in early stages of carcinogenesis. Proc. Natl Acad. Sci. USA 107, 10324–10329 (2010).
pubmed: 20479229
doi: 10.1073/pnas.1005283107
Kravchenko-Balasha, N., Shin, Y. S., Sutherland, A., Levine, R. D. & Heath, J. R. Intercellular signaling through secreted proteins induces free-energy gradient-directed cell movement. Proc. Natl Acad. Sci. USA 113, 5520–5525 (2016).
pubmed: 27140641
doi: 10.1073/pnas.1602171113
Kravchenko-Balasha, N., Wang, J., Remacle, F., Levine, R. D. & Heath, J. R. Glioblastoma cellular architectures are predicted through the characterization of two-cell interactions. Proc. Natl Acad. Sci. USA 111, 6521–6526 (2014).
pubmed: 24733941
doi: 10.1073/pnas.1404462111
Alter, O., Brown, P. O. & Botstein, D. Singular value decomposition for genome-wide expression data processing and modeling. Proc. Natl Acad. Sci. USA 97, 10101–10106 (2000).
pubmed: 10963673
doi: 10.1073/pnas.97.18.10101
Hoek, K. S. et al. In vivo switching of human melanoma cells between proliferative and invasive states. Cancer Res. 68, 650–656 (2008).
pubmed: 18245463
doi: 10.1158/0008-5472.CAN-07-2491
Müller, J. et al. Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma. Nat. Commun. 5, 5712 (2014).
Scheffer, M. Critical transitions in nature and society. Am. J. Psychol. https://doi.org/10.5406/amerjpsyc.124.3.0365 (2011).
Bargaje, R. et al. Cell population structure prior to bifurcation predicts efficiency of directed differentiation in human induced pluripotent cells. Proc. Natl Acad. Sci. USA 114, 2271–2276 (2017).
pubmed: 28167799
doi: 10.1073/pnas.1621412114
Mojtahedi, M. et al. Cell fate decision as high-dimensional critical state transition. PLoS Biol. 14, 1–13 (2016).
doi: 10.1371/journal.pbio.2000640
Richard, A. et al. Single-cell-based analysis highlights a surge in cell-to-cell molecular variability preceding irreversible commitment in a differentiation process. PLoS Biol. 14, (2016).
Su, Y. et al. Kinetic inference resolves epigenetic mechanism of drug resistance in melanoma. Preprint at https://www.biorxiv.org/content/10.1101/724740v1 (2020).
Lu, Y. et al. Highly multiplexed profiling of single-cell effector functions reveals deep functional heterogeneity in response to pathogenic ligands. Proc. Natl Acad. Sci. USA 112, E607–E615 (2015).
pubmed: 25646488
doi: 10.1073/pnas.1416756112
Li, Z. et al. Surface immobilization of redox-labile fluorescent probes: enabling single-cell co-profiling of aerobic glycolysis and oncogenic protein signaling activities. Angew. Chem. Int. Ed. 57, 11554–11558 (2018).
doi: 10.1002/anie.201803034
Xu, A. M. et al. Integrated measurement of intracellular proteins and transcripts in single cells. Lab Chip 18, 3251–3262 (2018).
pubmed: 30178802
pmcid: 6752714
doi: 10.1039/C8LC00639C
O’Connell, M. P. et al. Hypoxia induces phenotypic plasticity and therapy resistance in melanoma via the tyrosine kinase receptors ROR1 and ROR2. Cancer Discov. 3, 1378–1393 (2013).
pubmed: 24104062
pmcid: 3918498
doi: 10.1158/2159-8290.CD-13-0005
Smith, M. P. et al. Inhibiting drivers of non-mutational drug tolerance is a salvage strategy for targeted melanoma therapy. Cancer Cell 29, 270–284 (2016).
pubmed: 26977879
pmcid: 4796027
doi: 10.1016/j.ccell.2016.02.003
Konieczkowski, D. J. et al. A melanoma cell state distinction influences sensitivity to MAPK pathway inhibitors. Cancer Discov. 4, 816–827 (2014).
pubmed: 24771846
pmcid: 4154497
doi: 10.1158/2159-8290.CD-13-0424
Krolak-Schwedt, S. & Eckes, T. A graph theoretic criterion for determining the number of clusters in a data set. Multivar. Behav. Res. 27, 541–565 (1992).
doi: 10.1207/s15327906mbr2704_3